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Structure of this presentation List of issues covered by this presentation The measurement issue in GVC analysis The role played by foreign trade aggregated figures versus firm level data Is it feasible to develop GVC analysis using firm level foreign trade data? Some empirical examples Conclusions ….Global Value Chains (GVS) have emerged as a new analytical framework for a better understanding of the Globalisation of the industry…………but can we measure them? HOW FOREIGN TRADE DATA AT THE FIRM LEVEL CAN CONTRIBUTE TO A QUANTITATIVE AND IN DEPTH ASSESSMENT OF GVCs?

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The measurement issue in GVC analysis Global Value chain (GVC) has emerged in the business literature as a new analytical framework. It clearly shows that not only multinational enterprises (MNEs) but also specialised suppliers are key actors of global production fragmentation It is closely linked to the globalisation of production filieres, international networks of production, etc. Indeed, this concept is very sophisticated and complex, since it also includes dimensions like market power, global governance, etc It is an intrinsically dynamic and genuinely firm level concept: companies compete by continuously reshaping their position inside GVC Measurement of GVC is still an open issue. Aggregated indicators are based on foreign trade data and input output tables. Much of the firm level empirical evidence is based on qualitative assessment (case studies) or is model based with weak proxy variables.

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The role played by foreign trade aggregated figures versus firm level data International trade data play a crucial role as aggregated figures in the development of GVC indicators These indicators are based on intra-industry trade, intra-firm trade, intermediates trade, trade unit values. However, these aggregated indicators cannot support more analytical and complex analysis addressing strategic issue like moving up in a GVC Firm level foreign trade data can support more complex and flexible analysis of GVC based on a trade operator perspective In particular, trade operator data are very detailed (single transaction data including good characteristics, partner country) and can be linked to business characteristics (business register) and economic performance indicators (Structural business statistics micro-data). Information on the foreign trade operator non resident partner is also a crucial asset to improve our knowledge of GVC The analysis of GVC exclusively based on foreign trade operators data is limited to a truncated production network where a resident company is engaged in trade linkages with foreign companies only as direct GVC partners.

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Is it feasible to develop GVC analysis using firm level foreign trade data? Most EU member states have already developed figures on trade operator business characteristics. There is an ongoing Eurostat project with the goal of harmonising and expanding figures on business characteristics of trade operators. Some key non EU OECD countries, like US, have already developed similar figures. The basic framework to develop these new figures, based on the link between the trade operators register and the business register on all active resident companies, is usually available in most OECD countries. Further information can be exploited from this framework and finalised to the analysis of Global Value Chains A short-medium term goal can be the development of new figures on trade operators characteristics finalised to measure companies potentially engaged in GVCs: This is essentially a data reclassification problem A long term goal will involve more analytical analyses of firm level foreign trade data addressing issues like market power and moving up in a value chain

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Some empirical examples The project is still at a very preliminary stage of development. So no robust analytical or policy implications can be inferred from what folllows. However, preliminary empirical results seem to be very interesting and can represent a relevant asset for the empirical analysis of GVC As a first step, we have essentially reclassified trade operators linked to business register characteristics grouping trade flows by MIG. Different business profiles of trade operators emerge from this analysis based on trade characteristics from both export and import sides. We focus on medium and large size companies (50 plus person employed) actively engaged in external trade of intermediate goods from both exports and imports. We assume that these companies are potentially engaged in GVC We further expand this very preliminary analysis based on the dynamic of firm level export and import unit values for a sample of companies potentially engaged in GVC.

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Italian medium and large size firms potentially engaged in Global value chains ( companies active in trade of intermediate goods from both exports and imports as a share of total M-L size companies active in exports trade)

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Large and Medium size Italian firms active in trade in intermediate goods by number of foreign resident trade partners (intra-EU trade only)

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Firm level dynamic of export and import unit values for a sample of Italian LM size firms potentially engaged in GVS (unit value of the combined nomenclature code that is dominant from the export side in firm level trade of intermediate goods)

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Conclusions Firm level foreign trade trade can significantly contribute to the empirical analysis of global value chains. Most OECD countries have already set up a statistical framework for the production of statistics on trade operators business characteristics. Based on an agreed methodology, additional figures focusing on companies potentially engaged in GVC can be easily developed from this framework as a data reclassification work More analytical work can be done based on firm level trade data in order to explore complex issues like moving up in a GVC Further developments in this area will include additional linkages between the register of foreign trade operators with both national based (SBS data and economic accounts from administrative data sources) and international data sources (for instance ORBIS for foreign resident trade partner characteristics and performance indicators). So we can link firm level trade data (including unit values) with value added….........